Publications
522
Citations
14,207
Est. group size
~9
Recurring co-author estimate
Active years
43
Publishing since 1984
Charles A. Bouman works on computational imaging, developing mathematical and machine-learning methods to reconstruct high-quality images from raw sensor data, especially for X-ray CT, neutron imaging, and other scientific imaging systems. His work combines physics-based models of how imaging devices work with modern deep learning techniques to improve image quality, reduce noise, and speed up reconstruction. This research supports applications ranging from medical CT scanning to industrial and scientific imaging like neutron and dynamic radiography.
Publication output has fluctuated over the past decade, dropping from a peak around 2017-2018 to a lower level around 2019-2020, then partially recovering with moderate, fairly steady output (roughly 15-25 papers/year) in recent years.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Model Based Reconstruction for Hyperspectral Neutron Imaging
2025
- Total Variation Regularization for Tomographic Reconstruction of Cylindrically Symmetric Objects
arXiv (Cornell University) · 2024
- The Foundations of Computational Imaging: A signal processing perspective
IEEE Signal Processing Magazine · 2023
- TRINIDI: Time-of-Flight Resonance Imaging With Neutrons for Isotopic Density Inference
IEEE Transactions on Computational Imaging · 2023
- Physics guided machine learning for multi-material decomposition of tissues from dual-energy CT scans of simulated breast models with calcifications
Electronic Imaging · 2023
- TRINIDI: Time-of-Flight Resonance Imaging with Neutrons for Isotopic Density Inference
arXiv (Cornell University) · 2023
- Statistically Adaptive Filtering for Low Signal Correction in X-ray Computed Tomography
arXiv (Cornell University) · 2023
- MBIR Training for a 2.5D DL network in X-ray CT
arXiv (Cornell University) · 2023
- Design of Novel Loss Functions for Deep Learning in X-ray CT
arXiv (Cornell University) · 2023
- Foundations of Computational Imaging: A Model-Based Approach
Society for Industrial and Applied Mathematics eBooks · 2022
- High-precision inversion of dynamic radiography using hydrodynamic features
Optics Express · 2022
- CodEx: A Modular Framework for Joint Temporal De-Blurring and Tomographic Reconstruction
IEEE Transactions on Computational Imaging · 2022
- Design of novel loss functions for deep learning in x-ray CT
7th International Conference on Image Formation in X-Ray Computed Tomography · 2022
- A Noise Preserving Sharpening Filter for CT Image Enhancement
2022 IEEE International Conference on Image Processing (ICIP) · 2022
- Plug and play: a general approach for the fusion of sensor and machine learning models
OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 2022
- arXiv (Cornell University)×42
- IEEE Transactions on Computational Imaging×18
- Electronic Imaging×12
- Microscopy and Microanalysis×8
- IEEE Signal Processing Magazine×5
- Gregery T. Buzzard
Medicine · Purdue University West Lafayette
- Madhuri Nagare
Medicine · Purdue University West Lafayette
- Katherine Binzel
Medicine · The Ohio State University
- Jeffrey Martin
Medicine · Indiana University
- Zachary Smith
Medicine · The Ohio State University
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
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